Accurate measurement of the social context in which individuals live and interact is important for understanding many important well-being outcomes. Despite the relevance of neighborhood context and activity space data for social, behavioral, and medical research, several issues challenge the collection of data. First, precise spatial measures of neighborhood context and activity spaces are difficult to collect, particularly in settings without comprehensive number address systems. A second challenge to collecting neighborhood context and activity space data is that instruments have not taken full advantage of the visual cues, maps, and imagery that are likely to increase respondent spatial recall. This project's aims directly address these challenges. First, the project designs an innovative computer assisted interview (CAI) instrument that can easily be used by both interviewers and respondents. The instrument will be able to measure the location of features at whatever level of precision the respondent provides, from exact points to general spatial locations with higher degrees of uncertainty. Second, this project formally compares the quality of data collected using the CAI instrument to data collected using a standard paper-based instrument. Third, to demonstrate how these data can be used to advance knowledge, we test hypotheses comparing the overlap in residential neighborhood context and activity spaces among important population subgroups at our study site. The degree to which residential neighborhood context differs from activity spaces is an important factor because expanded activity spaces can be theorized as a mechanism of change. Our tests of hypotheses may suggest additional research in activity spaces as factors behind differentials in marriage, fertility, health-seeking, and othe behaviors that are rapidly changing in many developing settings. The project is able to meet these aims by taking advantage of the recent affordability of two important technologies: highly detailed field-based geographic information systems (GIS) and multi-touch displays. We expect this new tool to improve measurement methods for investigators who collect neighborhood context and activity space data.